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Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
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Phase transitions, KMS condition and decision making: an introductory model.

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Area of Science:

  • Statistical mechanics applied to social dynamics.
  • Interdisciplinary research bridging natural and social sciences.

Background:

  • Understanding collective decision-making in social systems.
  • Applying concepts from statistical physics to agent interactions.

Purpose of the Study:

  • To model interacting agents making binary choices ('yes'/'no').
  • To identify conditions for achieving consensus among agents.
  • To explore the use of KMS states and phase transitions in social contexts.

Main Methods:

  • Utilizing a mean-field Heisenberg model for agent interactions.
  • Describing agents using spin variables.
  • Applying the concept of KMS (Kubo-Martin-Schwinger) states.
  • Analyzing phase transitions in the social model.

Main Results:

  • Identified conditions under which agents reach a common choice.
  • Demonstrated the applicability of thermodynamic concepts to social behavior.
  • Showcased the emergence of collective behavior through interaction.

Conclusions:

  • KMS states and phase transitions provide a framework for understanding social consensus.
  • The model offers insights into collective decision-making dynamics.
  • This interdisciplinary approach highlights the power of physics in social science.